Predictive value of urinary cell cycle arrest biomarkers for all cause-acute kidney injury: a meta-analysis

The cell cycle arrest markers tissue inhibitor metalloproteinases-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) have been identified as potential biomarkers of acute kidney injury (AKI) in critically ill adults in intensive care units and cardiac surgery-associated AKI (CSA-AKI). However, the clinical impact on all-cause AKI remains unclear. Here, we report a meta-analysis performed to evaluate the predictive value of this biomarker for all-cause AKI. The PubMed, Cochrane, and EMBASE databases were systematically searched up to April 1, 2022. We used the Quality Assessment Tool for Diagnosis Accuracy Studies (QUADAS-2) to assess the quality. We extracted useful information from these studies and calculated the sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). Twenty studies with 3625 patients were included in the meta-analysis. The estimated sensitivity of urinary [TIMP-2] × [IGFBP7] in the diagnosis of all-cause AKI was 0.79 (95% CI 0.72, 0.84), and the specificity was 0.70 (95% CI 0.62, 0.76). The value of urine [TIMP-2] × [IGFBP7] in the early diagnosis of AKI was assessed using a random effects model. The pooled positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were 2.6 (95% CI 2.1, 3.3), 0.31 (95% CI 0.23, 0.40), and 8 (95% CI 6, 13), respectively. The AUROC was 0.81 (95% CI 0.78–0.84). No significant publication bias was observed in eligible studies. Subgroup analysis indicated that the diagnostic value was related to the severity of AKI, time measurement, and clinical setting. This study shows that urinary [TIMP-2] × [IGFBP7] is a reliable effective predictive test for all cause-AKI. However, whether and how urinary [TIMP-2] × [IGFBP7] can be used in clinical diagnosis still requires further research and clinical trials.

www.nature.com/scientificreports/ growth factor-binding protein 7 (IGFBP7) have been proposed for the early detection of cardiac surgery-associated acute kidney injury (CSA-AKI) 8 . Both are involved in the G1 cell cycle, which is a known mechanism of AKI 9 . In human kidneys, TIMP-2 is expressed in the distal nephron, whereas IGFBP7 is mainly expressed in the proximal tubule, and both markers can be detected in urine samples 10

Methods
Search strategy. A complete meta-analysis protocol was constructed in adherence with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards. We performed a comprehensive literature search of the MEDLINE, PubMed, and EMBASE databases from 2013 to April 2022 to identify relevant articles. The literature search included the keywords and MeSH (medical subject headings) terms "acute kidney injury", "acute renal failure", "acute tubular necrosis", "TIMP-2", or "Tissue Inhibitor of Metalloproteinase-2", "IGFBP7", "IGF-binding protein 7", "insulin-like growth factor binding protein 7", with no language restrictions. The full search strategy is provided in the Supplementary Document. The search strategy was manually adapted according to the citation lists of the retrieved articles for the sensitivity analysis. The reference lists of selected studies were manually searched to identify potentially relevant citations.

Study selection. Two investigators independently evaluated all identified articles for eligibility and inclu-
sion. Any disagreements were resolved by consultation with a third investigator. Although there were no initial language restrictions, for the full-text review and final analysis, we included only articles published in English. Studies included met the following criteria: (1) original study; (2)  Data extraction and quality assessment. Data on the patients and study characteristics were collected and entered into a database to assess study eligibility. If eligible, a standardized data extraction sheet was used for data extraction. The following data were extracted: first author, year of publication, publication data, study design, population type, age, sample size, test method, timing of measurement, AKI definition, sample storage, TP, FP, FN, TN, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). We assessed the methodological quality using the Quality Assessment Tool for Diagnosis Accuracy Studies (QUA-DAS-2) 12 . Any discrepancies that arose from the study selection, data extraction, and quality assessment were resolved by discussion to reach a final consensus.
Statistical analysis. All statistical analyses were conducted using Review Manager 5.4 (RevMan; The Cochrane Collaboration, Oxford, UK) and STATA 14.0 software (Stata Corp, LP, College Station, TX, USA).
A random-effects model or fixed-effects model was constructed to estimate the pooled sensitivity, specificity, pooled positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) with 95% CI. The model selection was based on the heterogeneity of the included studies 13 . Diagnostic accuracy analysis was consistent with the summary receiver operating characteristic (SROC) curve and area under the curve (AUC) of the SROC. The heterogeneity induced by the threshold effect was set at P < 0.05. Heterogeneity in the meta-analysis represented the degree of variation in the study results, and was assessed using Cochran's Q test and I 2 test 14 . Cochran's Q test indicated heterogeneity at P < 0.10, and I 2 > 50% was considered an indication of significant heterogeneity. A useful predictor of AKI risk was defined as an AUROC of > 0.7 and P < 0.05. The Fagan nomogram was used to calculate post-test probability (PTP). Deeks' funnel plot asymmetry test was used to check for publication bias using STATA 14.0 15 . All statistical tests were 2-sided, and statistical significance was set at P < 0.05.
Ethics approval and consent to participate. The local Institutional Review Board deemed the study exempt from review.

Results
Search results. A total of 200 articles were preliminarily identified through the search. First, 40 studies were removed after duplicates were identified. We excluded 120 studies by screening the titles and abstracts. After reviewing the full text of the remaining studies, a further 18 publications were excluded: 10 did not have the required data, 4 had no definition of AKI, 3 had unclear measurement time of biomarkers, and 1 had no male subjects. Moreover, two studies were unable to extract a 2 × 2 table data, but only AUROC prediction values 16,17 . Finally, 20 studies were included in the quantitative analysis ( Fig. 1) 10,11,18-35 . Study and patient characteristics. All studies were published between 2013 and 2022, and a total of 3625 patients were included in this meta-analysis. Quality assessment and publication bias. The quality outcomes of the included studies according to the QUADAS-2 are shown in Fig. 2. Our results revealed that 7 studies did not use a set threshold, resulting in a higher risk in the index test. Concerning the reference criteria, seven studies were assessed as having unclear risk because they did not mention blinding. None of the studies had concerns regarding applicability. Details of   www.nature.com/scientificreports/ which summary sensitivity (SENS) and specificity (SPEC) correspond is represented by the diamond shape, and the respective 95% confidence intervals, by the dashed line, whereas the 95% confidence area in which a new study will be located is represented by the dotted line.  Table 2.

Discussion
AKI is a common and severe clinical condition. Currently, the diagnosis of AKI is based on serum creatinine level and urine output; however, these diagnoses are insensitive, especially in the early stages of AKI. Serum creatinine levels do not rise until 24 to 72 h after kidney injury, and urine output is less specific and is also affected by diuretics. Over the past decades, many biomarkers, including neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule 1 (KIM-1), and interleukin 18 (IL18), have been studied for the early diagnosis of AKI, but their diagnostic sensitivity is relatively low [36][37][38] 40 . There have been many studies in various clinical settings for AKI (e.g. surgery-associated, cardiac arrest-associated, sepsis) and age groups (e.g. older adults vs. younger adults) were included in the analysis. Our study demonstrated that across various clinical contexts, a cutoff value of 0.3 was selected in 11 studies included in our analysis. When considering a predictive biomarker, it is crucial to establish a cutoff value that differentiates between disease and healthy groups. Unfortunately, we were unable to determine the optimal cutoff points for urine [TIMP-2] × [IGFBP7] due to the observed variation in cutoff values across the included studies. The large Sapphire and Opal cohorts have validated the cutoffs of 0.3 and 2.0 for moderate-to-severe AKI 18,19 . However, it remains an open question as to how clinicians can effectively utilize this potential in different clinical contexts. Table 2. Results of subgroup analysis based on different standards. AUROC area under the receiver operating characteristic curve, CI confidence interval, DOR diagnostic odds ratio, ED emergency department, ICU intensive care unit, PLR positive likelihood ratio, NLR negative likelihood ratio. www.nature.com/scientificreports/ TIMP-2 and IGFBP7 are two biomarkers of G1 phase cell cycle arrest. These factors act by blocking the binding of cyclin and protein kinases through regulation of the P53 and P21 signaling pathways and alteration of the response of cells to inflammatory factors and toxins 41 . AKI-induced increases in urinary TIMP2 and IFGBP7 are caused by increased filtration, reduced tubule reabsorption, and urinary leakage of TIMP2 and IGFBP7 from proximal tubule cells 42 44 , but there were only three studies in the "KDIGO stage 1" subgroup. AKI diagnosed by the KDIGO stage 1 criteria is affected by a variety of factors, including blood concentration and drugs; thus, it may only reflect pure functional impairment, without a true kidney injury having occured. TIMP-2 and IGFBP7 levels in the urine were elevated only when the kidney was in emergency or damaged conditions. Therefore, urine [TIMP-2] × [IGFBP7] may be more sensitive for predicting severe AKI (KDIGO stage 2 or 3).
Despite significant advances in the epidemiology of AKI, predicting kidney recovery after AKI remains a major clinical challenge. One study has shown that plasma NGAL can predict AKI recovery, but its predictive performance is limited 45 32 . The levels of cell cycle arrest biomarkers ([TIMP-2] × [IGFBP7]) increased with increasing AKI severity, indicating it could be used to monitor the progress of the condition. However, the severity of AKI is associated with a significantly increased incidence of clinically important outcomes such as renal replacement therapy, in-hospital mortality, and persistent renal dysfunction. Consequently, early detection and risk assessment could improve patient outcomes through early intervention and optimized patient management.
The present study had several limitations.

Conclusion
In conclusion, this meta-analysis included updated clinical studies and used more accurate analysis methods to assess the diagnostic value of urine [TIMP-2] × [IGFBP7] compared to the current literature. Our meta-analysis suggests that urinary [TIMP-2] × [IGFBP7] levels have good predictive value as biomarkers of AKI in a wide range of clinical settings. However, whether and how urinary [TIMP-2] × [IGFBP7] can be widely used in the clinical diagnosis of all-cause AKI needs to be studied in different clinical settings, patient populations, and disease spectrum studies in the future.

Data availability
All data relevant to the study are included in the article or uploaded as Supplementary Information. In addition, the datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.